{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Import nibabel package to read NIfTI images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nibabel.testing import data_path\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from keras import applications\n",
    "import nibabel as nib\n",
    "import keras"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Enable GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "config = tf.ConfigProto( device_count = {'GPU': 1 , 'CPU': 56} ) \n",
    "sess = tf.Session(config=config) \n",
    "keras.backend.set_session(sess)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check the GPU "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[name: \"/device:CPU:0\"\n",
      "device_type: \"CPU\"\n",
      "memory_limit: 268435456\n",
      "locality {\n",
      "}\n",
      "incarnation: 9735628767886619574\n",
      ", name: \"/device:XLA_GPU:0\"\n",
      "device_type: \"XLA_GPU\"\n",
      "memory_limit: 17179869184\n",
      "locality {\n",
      "}\n",
      "incarnation: 105923996741610659\n",
      "physical_device_desc: \"device: XLA_GPU device\"\n",
      ", name: \"/device:XLA_CPU:0\"\n",
      "device_type: \"XLA_CPU\"\n",
      "memory_limit: 17179869184\n",
      "locality {\n",
      "}\n",
      "incarnation: 1285804040333629308\n",
      "physical_device_desc: \"device: XLA_CPU device\"\n",
      ", name: \"/device:GPU:0\"\n",
      "device_type: \"GPU\"\n",
      "memory_limit: 11579215053\n",
      "locality {\n",
      "  bus_id: 1\n",
      "  links {\n",
      "  }\n",
      "}\n",
      "incarnation: 18341216715057400559\n",
      "physical_device_desc: \"device: 0, name: TITAN Xp, pci bus id: 0000:01:00.0, compute capability: 6.1\"\n",
      "]\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.python.client import device_lib \n",
    "print(device_lib.list_local_devices())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Import all the Keras required library "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import glob\n",
    "from keras.losses import categorical_crossentropy\n",
    "from keras.models import Sequential, Model \n",
    "from keras.layers import Dense, Conv2D, Dropout, Flatten, MaxPooling2D\n",
    "from keras import layers\n",
    "\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fatch all the preprocessed images from the folder , preprocessing is done in SPM (matlab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "Adni_normal_6_months=glob.glob('/home/kushpal/Kushpal/ADNI_Normal/Normal-m06-3.0T(27)/[0-9]*/*/*/*/w*')\n",
    "Adni_normal_12_months=glob.glob('/home/kushpal/Kushpal/ADNI_Normal/Normal-m12-3.0T(27)/[0-9]*/*/*/*/w*')\n",
    "Adni_normal_24_months=glob.glob('/home/kushpal/Kushpal/ADNI_Normal/Normal-m24-3.0T(27)/[0-9]*/*/*/*/w*')\n",
    "Adni_normal_36_months=glob.glob('/home/kushpal/Kushpal/ADNI_Normal/Normal-m36-3.0T(27)/[0-9]*/*/*/*/w*')\n",
    "\n",
    "Mci_bl_3_months=glob.glob('/home/kushpal/Kushpal/MCI/MCI-bl-3.0T (22)/[0-9]*/*/*/*/w*')\n",
    "Mci_6_months=glob.glob('/home/kushpal/Kushpal/MCI/MCI-m06-3.0T (22)/[0-9]*/*/*/*/w*')\n",
    "Mci_12_months=glob.glob('/home/kushpal/Kushpal/MCI/MCI-m12-3.0T (22)/[0-9]*/*/*/*/w*')\n",
    "Mci_24_months=glob.glob('/home/kushpal/Kushpal/MCI/MCI-m24-3.0T (22)/[0-9]*/*/*/*/w*')\n",
    "Mci_36_months=glob.glob('/home/kushpal/Kushpal/MCI/MCI-m36-3.0T (22)/[0-9]*/*/*/*/w*')\n",
    "\n",
    "Ad_bl_3_months=glob.glob('/home/kushpal/Kushpal/AD-bl-3.0T(22)/[0-9]*/*/*/*/w*')\n",
    "Ad_6_months=glob.glob('/home/kushpal/Kushpal/AD-m06-3.0T(22)/[0-9]*/*/*/*/w*')\n",
    "Ad_12_months=glob.glob('/home/kushpal/Kushpal/AD-m12-3.0T(22)/[0-9]*/*/*/*/w*')\n",
    "Ad_24_months=glob.glob('/home/kushpal/Kushpal/AD-m24-3.0T(22)/[0-9]*/*/*/*/w*')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Label all the images with the corresponding categories (0, 1,2), 0 = CN, 1 = MCI, 2 = AD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Adni_normal_image_X=[]\n",
    "Adni_normal_image_Y=[]\n",
    "for i in range(len(Adni_normal_6_months)):\n",
    "    newimg = nib.load(Adni_normal_6_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Adni_normal_image_X.append(data)\n",
    "    Adni_normal_image_Y.append(0)\n",
    "for i in range(len(Adni_normal_12_months)):\n",
    "    newimg = nib.load(Adni_normal_12_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Adni_normal_image_X.append(data)\n",
    "    Adni_normal_image_Y.append(0)\n",
    "    \n",
    "for i in range(len(Adni_normal_24_months)):\n",
    "    newimg = nib.load(Adni_normal_24_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Adni_normal_image_X.append(data)\n",
    "    Adni_normal_image_Y.append(0)\n",
    "for i in range(len(Adni_normal_36_months)):\n",
    "    newimg = nib.load(Adni_normal_36_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Adni_normal_image_X.append(data)\n",
    "    Adni_normal_image_Y.append(0)\n",
    "\n",
    "\n",
    "Mci_image_X=[]\n",
    "Mci_image_Y=[]\n",
    "for i in range(len(Mci_bl_3_months)):\n",
    "    newimg = nib.load(Mci_bl_3_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Mci_image_X.append(data)\n",
    "    Mci_image_Y.append(1)\n",
    "for i in range(len(Mci_6_months)):\n",
    "    newimg = nib.load(Mci_6_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Mci_image_X.append(data)\n",
    "    Mci_image_Y.append(1)\n",
    "for i in range(len(Mci_12_months)):\n",
    "    newimg = nib.load(Mci_12_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Mci_image_X.append(data)\n",
    "    Mci_image_Y.append(1)\n",
    "    \n",
    "for i in range(len(Mci_24_months)):\n",
    "    newimg = nib.load(Mci_24_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Mci_image_X.append(data)\n",
    "    Mci_image_Y.append(1)\n",
    "    \n",
    "for i in range(len(Mci_36_months)):\n",
    "    newimg = nib.load(Mci_36_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Mci_image_X.append(data)\n",
    "    Mci_image_Y.append(1)\n",
    "\n",
    "\n",
    "Ad_image_X=[]\n",
    "Ad_image_Y=[]\n",
    "for i in range(len(Ad_bl_3_months)):\n",
    "    newimg = nib.load(Ad_bl_3_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Ad_image_X.append(data)\n",
    "    Ad_image_Y.append(2)\n",
    "for i in range(len(Ad_6_months)):\n",
    "    newimg = nib.load(Ad_6_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Ad_image_X.append(data)\n",
    "    Ad_image_Y.append(2)\n",
    "for i in range(len(Ad_12_months)):\n",
    "    newimg = nib.load(Ad_12_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Ad_image_X.append(data)\n",
    "    Ad_image_Y.append(2)\n",
    "    \n",
    "for i in range(len(Ad_24_months)):\n",
    "    newimg = nib.load(Ad_24_months[i])\n",
    "    data = newimg.get_data()\n",
    "    Ad_image_X.append(data)\n",
    "    Ad_image_Y.append(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Total_data_X=[]\n",
    "Total_data_Y=[]\n",
    "for i in range(len(Adni_normal_image_X)):\n",
    "    Total_data_X.append(Adni_normal_image_X[i])\n",
    "    Total_data_Y.append(Adni_normal_image_Y[i])\n",
    "for i in range(len(Mci_image_X)):\n",
    "    Total_data_X.append(Mci_image_X[i])\n",
    "    Total_data_Y.append(Mci_image_Y[i])\n",
    "for i in range(len(Ad_image_X)):\n",
    "    Total_data_X.append(Ad_image_X[i])\n",
    "    Total_data_Y.append(Ad_image_Y[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Total no of 3D images (303 X 121 X 145 X 121)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "303"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(Total_data_X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Data Conversion from 3D to 2D and introduce 3 channels (RGB) because the predefined model always takes 2D images with 3 channels in Keras."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "Newdata=np.array(Total_data_X)\n",
    "maindata=np.stack([Newdata]*3, axis=-1)\n",
    "\n",
    "maindata=maindata.reshape(303*121,145,121,3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Label all the converted images with their corresponding category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_y=[]\n",
    "for i in range (len(Total_data_X)):\n",
    "    for j in range(121):\n",
    "        new_y.append(Total_data_Y[i])\n",
    "new_y=np.array(new_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### After the conversion of  3D images, total no of 2D images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((36663, 145, 121, 3), (36663,))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maindata.shape,new_y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Split the data into train and test in the 70:30 ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(maindata, new_y, test_size=0.33)\n",
    "X_train=np.array(X_train)\n",
    "y_train=np.array(y_train)\n",
    "x_train = X_train.reshape(X_train.shape[0], 145, 121, 3)\n",
    "\n",
    "input_shape = (145, 121,3)\n",
    "x_train = x_train.astype('float32')\n",
    "y_train = keras.utils.to_categorical(y_train)\n",
    "y_old_test=y_test\n",
    "y_test = keras.utils.to_categorical(y_test)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Use the ResNet152 model. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/kushpal/.local/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kushpal/.local/lib/python3.5/site-packages/ipykernel_launcher.py:11: UserWarning: Update your `Model` call to the Keras 2 API: `Model(outputs=Tensor(\"de..., inputs=Tensor(\"in...)`\n",
      "  # This is added back by InteractiveShellApp.init_path()\n"
     ]
    }
   ],
   "source": [
    "\n",
    "model = applications.ResNet152(weights = \"imagenet\", include_top=False, input_shape =input_shape)\n",
    "\n",
    "\n",
    "# Freeze the layers which you don't want to train. Here I am not freezing any layer.\n",
    "for layer in model.layers:\n",
    "    layer.trainable = True\n",
    "#Adding custom Layers \n",
    "x = model.output\n",
    "x = Flatten()(x)\n",
    "predictions = Dense(3, activation=\"softmax\")(x)\n",
    "model= Model(input = model.input, output = predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 145, 121, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1_pad (ZeroPadding2D)       (None, 151, 127, 3)  0           input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv1_conv (Conv2D)             (None, 73, 61, 64)   9472        conv1_pad[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1_bn (BatchNormalization)   (None, 73, 61, 64)   256         conv1_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv1_relu (Activation)         (None, 73, 61, 64)   0           conv1_bn[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "pool1_pad (ZeroPadding2D)       (None, 75, 63, 64)   0           conv1_relu[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "pool1_pool (MaxPooling2D)       (None, 37, 31, 64)   0           pool1_pad[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_1_conv (Conv2D)    (None, 37, 31, 64)   4160        pool1_pool[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_1_bn (BatchNormali (None, 37, 31, 64)   256         conv2_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_1_relu (Activation (None, 37, 31, 64)   0           conv2_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_conv (Conv2D)    (None, 37, 31, 64)   36928       conv2_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_bn (BatchNormali (None, 37, 31, 64)   256         conv2_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_2_relu (Activation (None, 37, 31, 64)   0           conv2_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_0_conv (Conv2D)    (None, 37, 31, 256)  16640       pool1_pool[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_3_conv (Conv2D)    (None, 37, 31, 256)  16640       conv2_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_0_bn (BatchNormali (None, 37, 31, 256)  1024        conv2_block1_0_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_3_bn (BatchNormali (None, 37, 31, 256)  1024        conv2_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_add (Add)          (None, 37, 31, 256)  0           conv2_block1_0_bn[0][0]          \n",
      "                                                                 conv2_block1_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block1_out (Activation)   (None, 37, 31, 256)  0           conv2_block1_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_1_conv (Conv2D)    (None, 37, 31, 64)   16448       conv2_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_1_bn (BatchNormali (None, 37, 31, 64)   256         conv2_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_1_relu (Activation (None, 37, 31, 64)   0           conv2_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_conv (Conv2D)    (None, 37, 31, 64)   36928       conv2_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_bn (BatchNormali (None, 37, 31, 64)   256         conv2_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_2_relu (Activation (None, 37, 31, 64)   0           conv2_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_3_conv (Conv2D)    (None, 37, 31, 256)  16640       conv2_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_3_bn (BatchNormali (None, 37, 31, 256)  1024        conv2_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_add (Add)          (None, 37, 31, 256)  0           conv2_block1_out[0][0]           \n",
      "                                                                 conv2_block2_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block2_out (Activation)   (None, 37, 31, 256)  0           conv2_block2_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_1_conv (Conv2D)    (None, 37, 31, 64)   16448       conv2_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_1_bn (BatchNormali (None, 37, 31, 64)   256         conv2_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_1_relu (Activation (None, 37, 31, 64)   0           conv2_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_conv (Conv2D)    (None, 37, 31, 64)   36928       conv2_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_bn (BatchNormali (None, 37, 31, 64)   256         conv2_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_2_relu (Activation (None, 37, 31, 64)   0           conv2_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_3_conv (Conv2D)    (None, 37, 31, 256)  16640       conv2_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_3_bn (BatchNormali (None, 37, 31, 256)  1024        conv2_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_add (Add)          (None, 37, 31, 256)  0           conv2_block2_out[0][0]           \n",
      "                                                                 conv2_block3_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv2_block3_out (Activation)   (None, 37, 31, 256)  0           conv2_block3_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_1_conv (Conv2D)    (None, 19, 16, 128)  32896       conv2_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_1_relu (Activation (None, 19, 16, 128)  0           conv3_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_2_relu (Activation (None, 19, 16, 128)  0           conv3_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_0_conv (Conv2D)    (None, 19, 16, 512)  131584      conv2_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_0_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block1_0_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_add (Add)          (None, 19, 16, 512)  0           conv3_block1_0_bn[0][0]          \n",
      "                                                                 conv3_block1_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block1_out (Activation)   (None, 19, 16, 512)  0           conv3_block1_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_1_relu (Activation (None, 19, 16, 128)  0           conv3_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_2_relu (Activation (None, 19, 16, 128)  0           conv3_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_add (Add)          (None, 19, 16, 512)  0           conv3_block1_out[0][0]           \n",
      "                                                                 conv3_block2_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block2_out (Activation)   (None, 19, 16, 512)  0           conv3_block2_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_1_relu (Activation (None, 19, 16, 128)  0           conv3_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_2_relu (Activation (None, 19, 16, 128)  0           conv3_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_add (Add)          (None, 19, 16, 512)  0           conv3_block2_out[0][0]           \n",
      "                                                                 conv3_block3_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block3_out (Activation)   (None, 19, 16, 512)  0           conv3_block3_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block4_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_1_relu (Activation (None, 19, 16, 128)  0           conv3_block4_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block4_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block4_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_2_relu (Activation (None, 19, 16, 128)  0           conv3_block4_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block4_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block4_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_add (Add)          (None, 19, 16, 512)  0           conv3_block3_out[0][0]           \n",
      "                                                                 conv3_block4_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block4_out (Activation)   (None, 19, 16, 512)  0           conv3_block4_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block4_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block5_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_1_relu (Activation (None, 19, 16, 128)  0           conv3_block5_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block5_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block5_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_2_relu (Activation (None, 19, 16, 128)  0           conv3_block5_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block5_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block5_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_add (Add)          (None, 19, 16, 512)  0           conv3_block4_out[0][0]           \n",
      "                                                                 conv3_block5_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block5_out (Activation)   (None, 19, 16, 512)  0           conv3_block5_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block5_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block6_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_1_relu (Activation (None, 19, 16, 128)  0           conv3_block6_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block6_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block6_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_2_relu (Activation (None, 19, 16, 128)  0           conv3_block6_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block6_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block6_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_add (Add)          (None, 19, 16, 512)  0           conv3_block5_out[0][0]           \n",
      "                                                                 conv3_block6_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block6_out (Activation)   (None, 19, 16, 512)  0           conv3_block6_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block6_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block7_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_1_relu (Activation (None, 19, 16, 128)  0           conv3_block7_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block7_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block7_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_2_relu (Activation (None, 19, 16, 128)  0           conv3_block7_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block7_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block7_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_add (Add)          (None, 19, 16, 512)  0           conv3_block6_out[0][0]           \n",
      "                                                                 conv3_block7_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block7_out (Activation)   (None, 19, 16, 512)  0           conv3_block7_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_1_conv (Conv2D)    (None, 19, 16, 128)  65664       conv3_block7_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_1_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block8_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_1_relu (Activation (None, 19, 16, 128)  0           conv3_block8_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_conv (Conv2D)    (None, 19, 16, 128)  147584      conv3_block8_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_bn (BatchNormali (None, 19, 16, 128)  512         conv3_block8_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_2_relu (Activation (None, 19, 16, 128)  0           conv3_block8_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_3_conv (Conv2D)    (None, 19, 16, 512)  66048       conv3_block8_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_3_bn (BatchNormali (None, 19, 16, 512)  2048        conv3_block8_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_add (Add)          (None, 19, 16, 512)  0           conv3_block7_out[0][0]           \n",
      "                                                                 conv3_block8_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv3_block8_out (Activation)   (None, 19, 16, 512)  0           conv3_block8_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_1_conv (Conv2D)    (None, 10, 8, 256)   131328      conv3_block8_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_1_relu (Activation (None, 10, 8, 256)   0           conv4_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_2_relu (Activation (None, 10, 8, 256)   0           conv4_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_0_conv (Conv2D)    (None, 10, 8, 1024)  525312      conv3_block8_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_0_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block1_0_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_add (Add)          (None, 10, 8, 1024)  0           conv4_block1_0_bn[0][0]          \n",
      "                                                                 conv4_block1_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block1_out (Activation)   (None, 10, 8, 1024)  0           conv4_block1_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_1_relu (Activation (None, 10, 8, 256)   0           conv4_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_2_relu (Activation (None, 10, 8, 256)   0           conv4_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_add (Add)          (None, 10, 8, 1024)  0           conv4_block1_out[0][0]           \n",
      "                                                                 conv4_block2_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block2_out (Activation)   (None, 10, 8, 1024)  0           conv4_block2_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_1_relu (Activation (None, 10, 8, 256)   0           conv4_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_2_relu (Activation (None, 10, 8, 256)   0           conv4_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_add (Add)          (None, 10, 8, 1024)  0           conv4_block2_out[0][0]           \n",
      "                                                                 conv4_block3_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block3_out (Activation)   (None, 10, 8, 1024)  0           conv4_block3_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block4_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_1_relu (Activation (None, 10, 8, 256)   0           conv4_block4_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block4_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block4_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_2_relu (Activation (None, 10, 8, 256)   0           conv4_block4_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block4_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block4_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_add (Add)          (None, 10, 8, 1024)  0           conv4_block3_out[0][0]           \n",
      "                                                                 conv4_block4_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block4_out (Activation)   (None, 10, 8, 1024)  0           conv4_block4_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block4_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block5_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_1_relu (Activation (None, 10, 8, 256)   0           conv4_block5_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block5_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block5_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_2_relu (Activation (None, 10, 8, 256)   0           conv4_block5_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block5_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block5_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_add (Add)          (None, 10, 8, 1024)  0           conv4_block4_out[0][0]           \n",
      "                                                                 conv4_block5_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block5_out (Activation)   (None, 10, 8, 1024)  0           conv4_block5_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block5_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block6_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_1_relu (Activation (None, 10, 8, 256)   0           conv4_block6_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block6_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block6_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_2_relu (Activation (None, 10, 8, 256)   0           conv4_block6_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block6_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block6_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_add (Add)          (None, 10, 8, 1024)  0           conv4_block5_out[0][0]           \n",
      "                                                                 conv4_block6_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block6_out (Activation)   (None, 10, 8, 1024)  0           conv4_block6_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block6_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block7_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_1_relu (Activation (None, 10, 8, 256)   0           conv4_block7_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block7_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block7_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_2_relu (Activation (None, 10, 8, 256)   0           conv4_block7_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block7_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block7_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_add (Add)          (None, 10, 8, 1024)  0           conv4_block6_out[0][0]           \n",
      "                                                                 conv4_block7_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block7_out (Activation)   (None, 10, 8, 1024)  0           conv4_block7_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block7_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block8_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_1_relu (Activation (None, 10, 8, 256)   0           conv4_block8_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block8_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block8_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_2_relu (Activation (None, 10, 8, 256)   0           conv4_block8_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block8_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block8_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_add (Add)          (None, 10, 8, 1024)  0           conv4_block7_out[0][0]           \n",
      "                                                                 conv4_block8_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block8_out (Activation)   (None, 10, 8, 1024)  0           conv4_block8_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_1_conv (Conv2D)    (None, 10, 8, 256)   262400      conv4_block8_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_1_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block9_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_1_relu (Activation (None, 10, 8, 256)   0           conv4_block9_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_conv (Conv2D)    (None, 10, 8, 256)   590080      conv4_block9_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_bn (BatchNormali (None, 10, 8, 256)   1024        conv4_block9_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_2_relu (Activation (None, 10, 8, 256)   0           conv4_block9_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_3_conv (Conv2D)    (None, 10, 8, 1024)  263168      conv4_block9_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_3_bn (BatchNormali (None, 10, 8, 1024)  4096        conv4_block9_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_add (Add)          (None, 10, 8, 1024)  0           conv4_block8_out[0][0]           \n",
      "                                                                 conv4_block9_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block9_out (Activation)   (None, 10, 8, 1024)  0           conv4_block9_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block9_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block10_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block10_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block10_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block10_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block10_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block10_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block10_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_add (Add)         (None, 10, 8, 1024)  0           conv4_block9_out[0][0]           \n",
      "                                                                 conv4_block10_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block10_out (Activation)  (None, 10, 8, 1024)  0           conv4_block10_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block10_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block11_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block11_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block11_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block11_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block11_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block11_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block11_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_add (Add)         (None, 10, 8, 1024)  0           conv4_block10_out[0][0]          \n",
      "                                                                 conv4_block11_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block11_out (Activation)  (None, 10, 8, 1024)  0           conv4_block11_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block11_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block12_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block12_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block12_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block12_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block12_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block12_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block12_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_add (Add)         (None, 10, 8, 1024)  0           conv4_block11_out[0][0]          \n",
      "                                                                 conv4_block12_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block12_out (Activation)  (None, 10, 8, 1024)  0           conv4_block12_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block12_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block13_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block13_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block13_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block13_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block13_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block13_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block13_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_add (Add)         (None, 10, 8, 1024)  0           conv4_block12_out[0][0]          \n",
      "                                                                 conv4_block13_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block13_out (Activation)  (None, 10, 8, 1024)  0           conv4_block13_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block13_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block14_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block14_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block14_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block14_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block14_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block14_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block14_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_add (Add)         (None, 10, 8, 1024)  0           conv4_block13_out[0][0]          \n",
      "                                                                 conv4_block14_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block14_out (Activation)  (None, 10, 8, 1024)  0           conv4_block14_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block14_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block15_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block15_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block15_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block15_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block15_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block15_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block15_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_add (Add)         (None, 10, 8, 1024)  0           conv4_block14_out[0][0]          \n",
      "                                                                 conv4_block15_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block15_out (Activation)  (None, 10, 8, 1024)  0           conv4_block15_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block15_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block16_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block16_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block16_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block16_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block16_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block16_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block16_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_add (Add)         (None, 10, 8, 1024)  0           conv4_block15_out[0][0]          \n",
      "                                                                 conv4_block16_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block16_out (Activation)  (None, 10, 8, 1024)  0           conv4_block16_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block16_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block17_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block17_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block17_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block17_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block17_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block17_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block17_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_add (Add)         (None, 10, 8, 1024)  0           conv4_block16_out[0][0]          \n",
      "                                                                 conv4_block17_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block17_out (Activation)  (None, 10, 8, 1024)  0           conv4_block17_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block17_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block18_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block18_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block18_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block18_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block18_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block18_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block18_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_add (Add)         (None, 10, 8, 1024)  0           conv4_block17_out[0][0]          \n",
      "                                                                 conv4_block18_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block18_out (Activation)  (None, 10, 8, 1024)  0           conv4_block18_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block18_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block19_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block19_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block19_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block19_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block19_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block19_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block19_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_add (Add)         (None, 10, 8, 1024)  0           conv4_block18_out[0][0]          \n",
      "                                                                 conv4_block19_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block19_out (Activation)  (None, 10, 8, 1024)  0           conv4_block19_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block19_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block20_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block20_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block20_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block20_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block20_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block20_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block20_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_add (Add)         (None, 10, 8, 1024)  0           conv4_block19_out[0][0]          \n",
      "                                                                 conv4_block20_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block20_out (Activation)  (None, 10, 8, 1024)  0           conv4_block20_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block20_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block21_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block21_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block21_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block21_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block21_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block21_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block21_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_add (Add)         (None, 10, 8, 1024)  0           conv4_block20_out[0][0]          \n",
      "                                                                 conv4_block21_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block21_out (Activation)  (None, 10, 8, 1024)  0           conv4_block21_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block21_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block22_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block22_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block22_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block22_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block22_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block22_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block22_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_add (Add)         (None, 10, 8, 1024)  0           conv4_block21_out[0][0]          \n",
      "                                                                 conv4_block22_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block22_out (Activation)  (None, 10, 8, 1024)  0           conv4_block22_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block22_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block23_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block23_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block23_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block23_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block23_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block23_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block23_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_add (Add)         (None, 10, 8, 1024)  0           conv4_block22_out[0][0]          \n",
      "                                                                 conv4_block23_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block23_out (Activation)  (None, 10, 8, 1024)  0           conv4_block23_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block23_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block24_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block24_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block24_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block24_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block24_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block24_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block24_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_add (Add)         (None, 10, 8, 1024)  0           conv4_block23_out[0][0]          \n",
      "                                                                 conv4_block24_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block24_out (Activation)  (None, 10, 8, 1024)  0           conv4_block24_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block24_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block25_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block25_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block25_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block25_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block25_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block25_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block25_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_add (Add)         (None, 10, 8, 1024)  0           conv4_block24_out[0][0]          \n",
      "                                                                 conv4_block25_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block25_out (Activation)  (None, 10, 8, 1024)  0           conv4_block25_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block25_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block26_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block26_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block26_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block26_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block26_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block26_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block26_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_add (Add)         (None, 10, 8, 1024)  0           conv4_block25_out[0][0]          \n",
      "                                                                 conv4_block26_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block26_out (Activation)  (None, 10, 8, 1024)  0           conv4_block26_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block26_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block27_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block27_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block27_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block27_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block27_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block27_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block27_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_add (Add)         (None, 10, 8, 1024)  0           conv4_block26_out[0][0]          \n",
      "                                                                 conv4_block27_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block27_out (Activation)  (None, 10, 8, 1024)  0           conv4_block27_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block27_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block28_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block28_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block28_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block28_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block28_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block28_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block28_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_add (Add)         (None, 10, 8, 1024)  0           conv4_block27_out[0][0]          \n",
      "                                                                 conv4_block28_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block28_out (Activation)  (None, 10, 8, 1024)  0           conv4_block28_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block28_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block29_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block29_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block29_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block29_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block29_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block29_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block29_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_add (Add)         (None, 10, 8, 1024)  0           conv4_block28_out[0][0]          \n",
      "                                                                 conv4_block29_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block29_out (Activation)  (None, 10, 8, 1024)  0           conv4_block29_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block29_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block30_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block30_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block30_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block30_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block30_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block30_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block30_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_add (Add)         (None, 10, 8, 1024)  0           conv4_block29_out[0][0]          \n",
      "                                                                 conv4_block30_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block30_out (Activation)  (None, 10, 8, 1024)  0           conv4_block30_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block30_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block31_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block31_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block31_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block31_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block31_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block31_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block31_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_add (Add)         (None, 10, 8, 1024)  0           conv4_block30_out[0][0]          \n",
      "                                                                 conv4_block31_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block31_out (Activation)  (None, 10, 8, 1024)  0           conv4_block31_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block31_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block32_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block32_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block32_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block32_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block32_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block32_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block32_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_add (Add)         (None, 10, 8, 1024)  0           conv4_block31_out[0][0]          \n",
      "                                                                 conv4_block32_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block32_out (Activation)  (None, 10, 8, 1024)  0           conv4_block32_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block32_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block33_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block33_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block33_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block33_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block33_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block33_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block33_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_add (Add)         (None, 10, 8, 1024)  0           conv4_block32_out[0][0]          \n",
      "                                                                 conv4_block33_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block33_out (Activation)  (None, 10, 8, 1024)  0           conv4_block33_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block33_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block34_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block34_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block34_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block34_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block34_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block34_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block34_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_add (Add)         (None, 10, 8, 1024)  0           conv4_block33_out[0][0]          \n",
      "                                                                 conv4_block34_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block34_out (Activation)  (None, 10, 8, 1024)  0           conv4_block34_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block34_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block35_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block35_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block35_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block35_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block35_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block35_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block35_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_add (Add)         (None, 10, 8, 1024)  0           conv4_block34_out[0][0]          \n",
      "                                                                 conv4_block35_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block35_out (Activation)  (None, 10, 8, 1024)  0           conv4_block35_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_1_conv (Conv2D)   (None, 10, 8, 256)   262400      conv4_block35_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_1_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block36_1_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_1_relu (Activatio (None, 10, 8, 256)   0           conv4_block36_1_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_conv (Conv2D)   (None, 10, 8, 256)   590080      conv4_block36_1_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_bn (BatchNormal (None, 10, 8, 256)   1024        conv4_block36_2_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_2_relu (Activatio (None, 10, 8, 256)   0           conv4_block36_2_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_3_conv (Conv2D)   (None, 10, 8, 1024)  263168      conv4_block36_2_relu[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_3_bn (BatchNormal (None, 10, 8, 1024)  4096        conv4_block36_3_conv[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_add (Add)         (None, 10, 8, 1024)  0           conv4_block35_out[0][0]          \n",
      "                                                                 conv4_block36_3_bn[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv4_block36_out (Activation)  (None, 10, 8, 1024)  0           conv4_block36_add[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_1_conv (Conv2D)    (None, 5, 4, 512)    524800      conv4_block36_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_1_bn (BatchNormali (None, 5, 4, 512)    2048        conv5_block1_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_1_relu (Activation (None, 5, 4, 512)    0           conv5_block1_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_conv (Conv2D)    (None, 5, 4, 512)    2359808     conv5_block1_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_bn (BatchNormali (None, 5, 4, 512)    2048        conv5_block1_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_2_relu (Activation (None, 5, 4, 512)    0           conv5_block1_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_0_conv (Conv2D)    (None, 5, 4, 2048)   2099200     conv4_block36_out[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_3_conv (Conv2D)    (None, 5, 4, 2048)   1050624     conv5_block1_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_0_bn (BatchNormali (None, 5, 4, 2048)   8192        conv5_block1_0_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_3_bn (BatchNormali (None, 5, 4, 2048)   8192        conv5_block1_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_add (Add)          (None, 5, 4, 2048)   0           conv5_block1_0_bn[0][0]          \n",
      "                                                                 conv5_block1_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block1_out (Activation)   (None, 5, 4, 2048)   0           conv5_block1_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_1_conv (Conv2D)    (None, 5, 4, 512)    1049088     conv5_block1_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_1_bn (BatchNormali (None, 5, 4, 512)    2048        conv5_block2_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_1_relu (Activation (None, 5, 4, 512)    0           conv5_block2_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_conv (Conv2D)    (None, 5, 4, 512)    2359808     conv5_block2_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_bn (BatchNormali (None, 5, 4, 512)    2048        conv5_block2_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_2_relu (Activation (None, 5, 4, 512)    0           conv5_block2_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_3_conv (Conv2D)    (None, 5, 4, 2048)   1050624     conv5_block2_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_3_bn (BatchNormali (None, 5, 4, 2048)   8192        conv5_block2_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_add (Add)          (None, 5, 4, 2048)   0           conv5_block1_out[0][0]           \n",
      "                                                                 conv5_block2_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block2_out (Activation)   (None, 5, 4, 2048)   0           conv5_block2_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_1_conv (Conv2D)    (None, 5, 4, 512)    1049088     conv5_block2_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_1_bn (BatchNormali (None, 5, 4, 512)    2048        conv5_block3_1_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_1_relu (Activation (None, 5, 4, 512)    0           conv5_block3_1_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_conv (Conv2D)    (None, 5, 4, 512)    2359808     conv5_block3_1_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_bn (BatchNormali (None, 5, 4, 512)    2048        conv5_block3_2_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_2_relu (Activation (None, 5, 4, 512)    0           conv5_block3_2_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_3_conv (Conv2D)    (None, 5, 4, 2048)   1050624     conv5_block3_2_relu[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_3_bn (BatchNormali (None, 5, 4, 2048)   8192        conv5_block3_3_conv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_add (Add)          (None, 5, 4, 2048)   0           conv5_block2_out[0][0]           \n",
      "                                                                 conv5_block3_3_bn[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "conv5_block3_out (Activation)   (None, 5, 4, 2048)   0           conv5_block3_add[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "flatten_1 (Flatten)             (None, 40960)        0           conv5_block3_out[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 3)            122883      flatten_1[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 58,493,827\n",
      "Trainable params: 58,342,403\n",
      "Non-trainable params: 151,424\n",
      "__________________________________________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compile and train the model with Adam optimizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/kushpal/.local/lib/python3.5/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.cast instead.\n",
      "Train on 22107 samples, validate on 2457 samples\n",
      "Epoch 1/50\n",
      "22107/22107 [==============================] - 201s 9ms/step - loss: 1.0305 - acc: 0.5340 - val_loss: 0.7011 - val_acc: 0.6862\n",
      "Epoch 2/50\n",
      "22107/22107 [==============================] - 152s 7ms/step - loss: 0.4748 - acc: 0.7750 - val_loss: 0.5106 - val_acc: 0.7566\n",
      "Epoch 3/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.3473 - acc: 0.8282 - val_loss: 0.4208 - val_acc: 0.7900\n",
      "Epoch 4/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.3017 - acc: 0.8434 - val_loss: 0.3982 - val_acc: 0.8030\n",
      "Epoch 5/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2762 - acc: 0.8547 - val_loss: 0.3618 - val_acc: 0.8164\n",
      "Epoch 6/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2635 - acc: 0.8588 - val_loss: 0.3708 - val_acc: 0.8201\n",
      "Epoch 7/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2584 - acc: 0.8579 - val_loss: 0.3735 - val_acc: 0.8144\n",
      "Epoch 8/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2473 - acc: 0.8613 - val_loss: 0.3826 - val_acc: 0.8189\n",
      "Epoch 9/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2463 - acc: 0.8616 - val_loss: 0.3639 - val_acc: 0.8168\n",
      "Epoch 10/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2492 - acc: 0.8628 - val_loss: 0.4201 - val_acc: 0.7981\n",
      "Epoch 11/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2520 - acc: 0.8584 - val_loss: 0.3730 - val_acc: 0.8205\n",
      "Epoch 12/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2474 - acc: 0.8615 - val_loss: 0.3663 - val_acc: 0.8193\n",
      "Epoch 13/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2495 - acc: 0.8644 - val_loss: 0.3752 - val_acc: 0.8148\n",
      "Epoch 14/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2449 - acc: 0.8641 - val_loss: 0.5410 - val_acc: 0.7733\n",
      "Epoch 15/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2431 - acc: 0.8645 - val_loss: 0.3325 - val_acc: 0.8291\n",
      "Epoch 16/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2307 - acc: 0.8658 - val_loss: 0.3576 - val_acc: 0.8327\n",
      "Epoch 17/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2309 - acc: 0.8674 - val_loss: 0.3565 - val_acc: 0.8287\n",
      "Epoch 18/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2400 - acc: 0.8652 - val_loss: 0.3899 - val_acc: 0.8128\n",
      "Epoch 19/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2486 - acc: 0.8603 - val_loss: 0.3725 - val_acc: 0.8225\n",
      "Epoch 20/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2405 - acc: 0.8641 - val_loss: 0.3290 - val_acc: 0.8368\n",
      "Epoch 21/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2299 - acc: 0.8676 - val_loss: 0.3358 - val_acc: 0.8319\n",
      "Epoch 22/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2277 - acc: 0.8686 - val_loss: 0.3401 - val_acc: 0.8344\n",
      "Epoch 23/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2300 - acc: 0.8686 - val_loss: 0.3654 - val_acc: 0.8217\n",
      "Epoch 24/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2402 - acc: 0.8672 - val_loss: 0.3982 - val_acc: 0.8160\n",
      "Epoch 25/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2471 - acc: 0.8633 - val_loss: 0.3591 - val_acc: 0.8307\n",
      "Epoch 26/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2316 - acc: 0.8676 - val_loss: 0.3358 - val_acc: 0.8335\n",
      "Epoch 27/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2285 - acc: 0.8683 - val_loss: 0.4218 - val_acc: 0.8112\n",
      "Epoch 28/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2299 - acc: 0.8673 - val_loss: 0.3962 - val_acc: 0.8217\n",
      "Epoch 29/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2367 - acc: 0.8661 - val_loss: 0.3377 - val_acc: 0.8384\n",
      "Epoch 30/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2306 - acc: 0.8666 - val_loss: 0.3423 - val_acc: 0.8376\n",
      "Epoch 31/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2274 - acc: 0.8697 - val_loss: 0.3379 - val_acc: 0.8396\n",
      "Epoch 32/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2267 - acc: 0.8686 - val_loss: 0.3481 - val_acc: 0.8380\n",
      "Epoch 33/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2339 - acc: 0.8668 - val_loss: 0.3774 - val_acc: 0.8266\n",
      "Epoch 34/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2349 - acc: 0.8655 - val_loss: 0.3776 - val_acc: 0.8262\n",
      "Epoch 35/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2279 - acc: 0.8698 - val_loss: 0.3741 - val_acc: 0.8339\n",
      "Epoch 36/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2269 - acc: 0.8678 - val_loss: 0.3441 - val_acc: 0.8356\n",
      "Epoch 37/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2272 - acc: 0.8689 - val_loss: 0.3527 - val_acc: 0.8384\n",
      "Epoch 38/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2306 - acc: 0.8685 - val_loss: 0.3366 - val_acc: 0.8364\n",
      "Epoch 39/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2282 - acc: 0.8681 - val_loss: 0.4050 - val_acc: 0.8225\n",
      "Epoch 40/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2341 - acc: 0.8674 - val_loss: 0.3748 - val_acc: 0.8311\n",
      "Epoch 41/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2270 - acc: 0.8681 - val_loss: 0.3583 - val_acc: 0.8360\n",
      "Epoch 42/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2241 - acc: 0.8703 - val_loss: 0.3636 - val_acc: 0.8400\n",
      "Epoch 43/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2227 - acc: 0.8701 - val_loss: 0.3274 - val_acc: 0.8433\n",
      "Epoch 44/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2228 - acc: 0.8717 - val_loss: 0.3348 - val_acc: 0.8417\n",
      "Epoch 45/50\n",
      "22107/22107 [==============================] - 154s 7ms/step - loss: 0.2293 - acc: 0.8696 - val_loss: 0.5110 - val_acc: 0.8067\n",
      "Epoch 46/50\n",
      "22107/22107 [==============================] - 155s 7ms/step - loss: 0.2389 - acc: 0.8643 - val_loss: 0.3709 - val_acc: 0.8311\n",
      "Epoch 47/50\n",
      "22107/22107 [==============================] - 153s 7ms/step - loss: 0.2267 - acc: 0.8685 - val_loss: 0.3522 - val_acc: 0.8380\n",
      "Epoch 48/50\n",
      "22107/22107 [==============================] - 153s 7ms/step - loss: 0.2235 - acc: 0.8714 - val_loss: 0.4011 - val_acc: 0.8295\n",
      "Epoch 49/50\n",
      "22107/22107 [==============================] - 152s 7ms/step - loss: 0.2276 - acc: 0.8695 - val_loss: 0.3973 - val_acc: 0.8344\n",
      "Epoch 50/50\n",
      "22107/22107 [==============================] - 147s 7ms/step - loss: 0.2229 - acc: 0.8731 - val_loss: 0.3578 - val_acc: 0.8400\n"
     ]
    }
   ],
   "source": [
    "model.compile(keras.optimizers.Adam(lr=1e-5), loss='categorical_crossentropy', metrics=['accuracy'])\n",
    "val=model.fit(x=x_train,y=y_train,batch_size=60, epochs=50,validation_split=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The model loss and accuracy on test data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of images in x_test 12099\n",
      "12099/12099 [==============================] - 29s 2ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.35156932543876673, 0.8394908670138028]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test=np.array(X_test)\n",
    "x_test = X_test.reshape(X_test.shape[0],145,121,3)\n",
    "x_test = x_test.astype('float32')\n",
    "print('Number of images in x_test', x_test.shape[0])\n",
    "model.evaluate(x_test,y_test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Accuracy')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(val.history['acc'])\n",
    "plt.plot(val.history['val_acc'])\n",
    "plt.legend(['Training accuracy' ,'Validation Accuracy'])\n",
    "plt.title(\"Train Vs Validation ACC With ResNet\")\n",
    "plt.xlabel(\"# of Epoch\")\n",
    "plt.ylabel(\"Accuracy\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
